Comparative molecular field analysis using molecular integral equation theory

Samiul M. Ansari, David S. Palmer

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Recently, Güssregen et al. used solute–solvent distribution functions calculated by the 3D Reference Interaction Site Model (3DRISM) in a 3D-QSAR model to predict the binding affinities of serine protease inhibitors; this approach was referred to as Comparative Analysis of 3D RISM MAps (CARMa). [J. Chem. Inf. Model., 2017, 57, 1652-1666] Here we extend this idea by introducing probe atoms into the 3DRISM solvent model in order to directly capture other molecular interactions in addition to those related to hydration/dehydration. Benchmark results for six different protein- ligand systems show that CARMa models trained on probe atom descriptors gives consistently more accurate predictions than CoMFA, and other common QSAR approaches.
LanguageEnglish
Number of pages40
JournalJournal of Chemical Information and Modeling
Early online date15 Mar 2018
DOIs
Publication statusE-pub ahead of print - 15 Mar 2018

Fingerprint

Integral equations
interaction
Atoms
Serine Proteinase Inhibitors
Molecular interactions
Dehydration
Hydration
Distribution functions
Ligands
Proteins

Keywords

  • genetic algorithm
  • partial least squares
  • binding affinity
  • molecular modelling

Cite this

@article{33794fa2af894d93a22b9da71b045a0e,
title = "Comparative molecular field analysis using molecular integral equation theory",
abstract = "Recently, Güssregen et al. used solute–solvent distribution functions calculated by the 3D Reference Interaction Site Model (3DRISM) in a 3D-QSAR model to predict the binding affinities of serine protease inhibitors; this approach was referred to as Comparative Analysis of 3D RISM MAps (CARMa). [J. Chem. Inf. Model., 2017, 57, 1652-1666] Here we extend this idea by introducing probe atoms into the 3DRISM solvent model in order to directly capture other molecular interactions in addition to those related to hydration/dehydration. Benchmark results for six different protein- ligand systems show that CARMa models trained on probe atom descriptors gives consistently more accurate predictions than CoMFA, and other common QSAR approaches.",
keywords = "genetic algorithm, partial least squares, binding affinity, molecular modelling",
author = "Ansari, {Samiul M.} and Palmer, {David S.}",
year = "2018",
month = "3",
day = "15",
doi = "10.1021/acs.jcim.7b00600",
language = "English",
journal = "Journal of Chemical Information and Modeling",
issn = "1549-9596",
publisher = "American Chemical Society",

}

TY - JOUR

T1 - Comparative molecular field analysis using molecular integral equation theory

AU - Ansari, Samiul M.

AU - Palmer, David S.

PY - 2018/3/15

Y1 - 2018/3/15

N2 - Recently, Güssregen et al. used solute–solvent distribution functions calculated by the 3D Reference Interaction Site Model (3DRISM) in a 3D-QSAR model to predict the binding affinities of serine protease inhibitors; this approach was referred to as Comparative Analysis of 3D RISM MAps (CARMa). [J. Chem. Inf. Model., 2017, 57, 1652-1666] Here we extend this idea by introducing probe atoms into the 3DRISM solvent model in order to directly capture other molecular interactions in addition to those related to hydration/dehydration. Benchmark results for six different protein- ligand systems show that CARMa models trained on probe atom descriptors gives consistently more accurate predictions than CoMFA, and other common QSAR approaches.

AB - Recently, Güssregen et al. used solute–solvent distribution functions calculated by the 3D Reference Interaction Site Model (3DRISM) in a 3D-QSAR model to predict the binding affinities of serine protease inhibitors; this approach was referred to as Comparative Analysis of 3D RISM MAps (CARMa). [J. Chem. Inf. Model., 2017, 57, 1652-1666] Here we extend this idea by introducing probe atoms into the 3DRISM solvent model in order to directly capture other molecular interactions in addition to those related to hydration/dehydration. Benchmark results for six different protein- ligand systems show that CARMa models trained on probe atom descriptors gives consistently more accurate predictions than CoMFA, and other common QSAR approaches.

KW - genetic algorithm

KW - partial least squares

KW - binding affinity

KW - molecular modelling

UR - https://pubs.acs.org/doi/10.1021/acs.jcim.7b00600

U2 - 10.1021/acs.jcim.7b00600

DO - 10.1021/acs.jcim.7b00600

M3 - Article

JO - Journal of Chemical Information and Modeling

T2 - Journal of Chemical Information and Modeling

JF - Journal of Chemical Information and Modeling

SN - 1549-9596

ER -